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Stride-by-stride gait spatio-temporal parameters estimate from shank-worn IMU recordings: validation on parkinson, choreic, hemiparetic and healthy elderly subjects

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Conference Paper
Movement contains a large amount of cognitive, central-motor and musculoskeletal information that correlates directly with the general state of health. Approaches to automatic movement analysis, in particular to automatized gait analysis are of utmost relevance to offer modern technological support for health professionals. The purpose of this paper is to present the experimental setup and preliminary results of the viability test of the TEDIPA study, which will evaluate the comparability of Azure Kinect's consumer depth and color camera with the medical product for gait analysis GAITRite, regarding accuracy and precision when measuring key indicators of healthy and pathological gait.
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The estimation of the spatio-temporal gait parameters is of primary importance in both physical activity monitoring and clinical contexts. A method for estimating step length bilaterally, during level walking, using a single inertial measurement unit (IMU) attached to the pelvis is proposed. In contrast to previous studies, based either on a simplified representation of the human gait mechanics or on a general linear regressive model, the proposed method estimates the step length directly from the integration of the acceleration along the direction of progression. The IMU was placed at pelvis level fixed to the subject's belt on the right side. The method was validated using measurements from a stereo-photogrammetric system as a gold standard on nine subjects walking ten laps along a closed loop track of about 25 m, varying their speed. For each loop, only the IMU data recorded in a 4 m long portion of the track included in the calibrated volume of the SP system, were used for the analysis. The method takes advantage of the cyclic nature of gait and it requires an accurate determination of the foot contact instances. A combination of a Kalman filter and of an optimally filtered direct and reverse integration applied to the IMU signals formed a single novel method (Kalman and Optimally filtered Step length Estimation - KOSE method). A correction of the IMU displacement due to the pelvic rotation occurring in gait was implemented to estimate the step length and the traversed distance. The step length was estimated for all subjects with less than 3% error. Traversed distance was assessed with less than 2% error. The proposed method provided estimates of step length and traversed distance more accurate than any other method applied to measurements obtained from a single IMU that can be found in the literature. In healthy subjects, it is reasonable to expect that, errors in traversed distance estimation during daily monitoring activity would be of the same order of magnitude of those presented.
  • A Salarian
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  • S Yang
S. Yang et al., Gait & Posture 2013, 37:354-8